code: def dump_model_norms(self, tag):
      actor_model_norm = get_model_norm(self.actor_model)
      ref_model_norm = get_model_norm(self.ref_model)
      critic_model_norm = get_model_norm(self.critic_model)
      reward_model_norm = get_model_norm(self.reward_model)
      print_all_ranks(
          f"{tag} global_actor_model_norm",
          actor_model_norm,
          self.args.local_rank,
      )
      print_all_ranks(
          f"{tag} global_ref_model_norm",
          ref_model_norm,
          self.args.local_rank,
      )
      print_all_ranks(
          f"{tag} global_critic_model_norm",
          critic_model_norm,
          self.args.local_rank,
      )
      print_all_ranks(
          f"{tag} global_reward_model_norm",
          reward_model_norm,
          self.args.local_rank,
      )
  
imports: import torch
  import torch.nn.functional
  import time
  import deepspeed
  from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus
  from deepspeed.accelerator import get_accelerator
  from dschat.utils.utils import print_rank_0
label_desc: Use image node_id 14 for calling the DeepSpeedPPOTrainer obj's underlying member method code with example usage: obj.dump_model_norms(tag) without return types